Arthur Gretton

Generating author description...

All published works

Action	Title	Year	Authors
+ PDF Chat	Accelerated Diffusion Models via Speculative Sampling	2025	Valentin De Bortoli Alexandre Galashov Arthur Gretton Arnaud Doucet
+ PDF Chat	Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression	2025	Juno Kim Dimitri Meunier Arthur Gretton Taiji Suzuki Zhu Li
+ PDF Chat	Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation	2024	Eleni Sgouritsa Virginia Aglietti Yee Whye Teh Arnaud Doucet Arthur Gretton Silvia Chiappa
+ PDF Chat	Nonparametric Instrumental Regression via Kernel Methods is Minimax Optimal	2024	Dimitri Meunier Zhu Li Timothy Christensen Arthur Gretton
+ PDF Chat	Spectral Representations for Accurate Causal Uncertainty Quantification with Gaussian Processes	2024	Hugh Dance Peter Orbanz Arthur Gretton
+ PDF Chat	Credal Two-Sample Tests of Epistemic Ignorance	2024	Siu Lun Chau Antonin Schrab Arthur Gretton Dino Sejdinović Krikamol Muandet
+ PDF Chat	(De)-regularized Maximum Mean Discrepancy Gradient Flow	2024	Zonghao Chen Aratrika Mustafi Pierre Glaser Anna Korba Arthur Gretton Bharath K. Sriperumbudur
+ PDF Chat	Foundations of Multivariate Distributional Reinforcement Learning	2024	Harley Wiltzer Jesse Farebrother Arthur Gretton Mark Rowland
+ PDF Chat	Spectral Representation for Causal Estimation with Hidden Confounders	2024	Tongzheng Ren Haotian Sun Antoine Moulin Arthur Gretton Bo Dai
+ PDF Chat	Mind the Graph When Balancing Data for Fairness or Robustness	2024	Jessica Schrouff Alexis Bellot Amal Rannen-Triki Alan Malek Isabela Albuquerque Arthur Gretton Alexander D’Amour Silvia Chiappa
+ PDF Chat	Conditional Bayesian Quadrature	2024	Zonghao Chen Masha Naslidnyk Arthur Gretton François‐Xavier Briol
+ PDF Chat	Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms	2024	Dimitri Meunier Zikai Shen Mattes Mollenhauer Arthur Gretton Li Zhu
+ PDF Chat	Deep MMD Gradient Flow without adversarial training	2024	Alexandre Galashov Valentin De Bortoli Arthur Gretton
+ PDF Chat	Proxy Methods for Domain Adaptation	2024	Katherine Tsai Stephen Pfohl Olawale Salaudeen Nicole Chiou Matt J. Kusner Alexander D’Amour Oluwasanmi Koyejo Arthur Gretton
+ PDF Chat	Practical Kernel Tests of Conditional Independence	2024	Roman Pogodin Antonin Schrab Yazhe Li Danica J. Sutherland Arthur Gretton
+ PDF Chat	A Distributional Analogue to the Successor Representation	2024	Harley Wiltzer Jesse Farebrother Arthur Gretton Yunhao Tang André Barreto Will Dabney Marc G. Bellemare Mark Rowland
+	Discussion of `Multiscale Fisher's Independence Test for Multivariate Dependence'	2023	Antonin Schrab Wittawat Jitkrittum Zoltán Szabó Dino Sejdinović Arthur Gretton
+ PDF Chat	Kernel methods for causal functions: dose, heterogeneous and incremental response curves	2023	Rahul Singh Liying Xu Arthur Gretton
+ PDF Chat	Kernel Methods for Multistage Causal Inference: Mediation Analysis and Dynamic Treatment Effects	2023	Rahul Singh Liyuan Xu Arthur Gretton
+ PDF Chat	A kernel Stein test for comparing latent variable models	2023	Heishiro Kanagawa Wittawat Jitkrittum Lester Mackey Kenji Fukumizu Arthur Gretton
+	Deep Hypothesis Tests Detect Clinically Relevant Subgroup Shifts in Medical Images	2023	Lisa M. Koch Christian M. Schürch Christian F. Baumgartner Arthur Gretton Philipp Berens
+	MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting	2023	Felix Biggs Antonin Schrab Arthur Gretton
+	Prediction under Latent Subgroup Shifts with High-Dimensional Observations	2023	William I. Walker Arthur Gretton Maneesh Sahani
+	Nonlinear Meta-Learning Can Guarantee Faster Rates	2023	Dimitri Meunier Li Zhu Arthur Gretton Samory Kpotufe
+	Kernel Single Proxy Control for Deterministic Confounding	2023	Liyuan Xu Arthur Gretton
+	Distributional Bellman Operators over Mean Embeddings	2023	Li Kevin Wenliang Grégoire Delétang Matthew Aitchison Marcus Hütter Anian Ruoss Arthur Gretton Mark Rowland
+	Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm	2023	Zhu Li Dimitri Meunier Mattes Mollenhauer Arthur Gretton
+ PDF Chat	Stein’s Method Meets Computational Statistics: A Review of Some Recent Developments	2022	Andreas Anastasiou Alessandro Barp François‐Xavier Briol Bruno Ebner Robert E. Gaunt Fatemeh Ghaderinezhad Jackson Gorham Arthur Gretton Christophe Ley Qiang Liu
+ PDF Chat	Discussion of ‘Multi-scale Fisher’s independence test for multivariate dependence’	2022	Antonin Schrab Wittawat Jitkrittum Zoltán Szabó Dino Sejdinović Arthur Gretton
+ PDF Chat	KSD Aggregated Goodness-of-fit Test	2022	Antonin Schrab Benjamin Guedj Arthur Gretton
+	Importance Weighting Approach in Kernel Bayes' Rule	2022	Liyuan Xu Yutian Chen Arnaud Doucet Arthur Gretton
+	KSD Aggregated Goodness-of-fit Test	2022	Antonin Schrab Benjamin Guedj Arthur Gretton
+	Efficient Aggregated Kernel Tests using Incomplete $U$-statistics	2022	Antonin Schrab Ilmun Kim Benjamin Guedj Arthur Gretton
+	Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach	2022	Yuchen Zhu Limor Gultchin Arthur Gretton Matt J. Kusner Ricardo Silva
+	Optimal Rates for Regularized Conditional Mean Embedding Learning	2022	Zhu Li Dimitri Meunier Mattes Mollenhauer Arthur Gretton
+	A Neural Mean Embedding Approach for Back-door and Front-door Adjustment	2022	Liyuan Xu Arthur Gretton
+	Maximum Likelihood Learning of Unnormalized Models for Simulation-Based Inference	2022	Pierre Glaser Michael Arbel Arnaud Doucet Arthur Gretton
+	Controlling Moments with Kernel Stein Discrepancies	2022	Heishiro Kanagawa Arthur Gretton Lester Mackey
+	Efficient Conditionally Invariant Representation Learning	2022	Roman Pogodin Namrata Deka Yazhe Li Danica J. Sutherland Victor Veitch Arthur Gretton
+	Adapting to Latent Subgroup Shifts via Concepts and Proxies	2022	Ibrahim Alabdulmohsin Nicole Chiou Alexander D’Amour Arthur Gretton Sanmi Koyejo Matt J. Kusner Stephen Pfohl Olawale Salaudeen Jessica Schrouff Katherine Tsai
+	A kernel Stein test of goodness of fit for sequential models	2022	Jerome Baum Heishiro Kanagawa Arthur Gretton
+	Deep Layer-wise Networks Have Closed-Form Weights	2022	Chieh Wu Aria Masoomi Arthur Gretton Jennifer Dy
+ PDF Chat	KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support	2021	Pierre Glaser Michael Arbel Arthur Gretton
+	Self-Supervised Learning with Kernel Dependence Maximization	2021	Yazhe Li Roman Pogodin Danica J. Sutherland Arthur Gretton
+	Composite Goodness-of-fit Tests with Kernels.	2021	Oscar Key Tamara Fernández Arthur Gretton François‐Xavier Briol
+ PDF Chat	Kernel Methods for Multistage Causal Inference: Mediation Analysis and Dynamic Treatment Effects	2021	Rahul Singh Liyuan Xu Arthur Gretton
+ PDF Chat	MMD Aggregated Two-Sample Test	2021	Antonin Schrab Ilmun Kim Mélisande Albert Béatrice Laurent Benjamin Guedj Arthur Gretton
+ PDF Chat	A Kernel Log-Rank Test of Independence for Right-Censored Data	2021	Tamara Fernández Arthur Gretton David Rindt Dino Sejdinović
+	Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction	2021	Afsaneh Mastouri Yuchen Zhu Limor Gultchin Anna Korba Ricardo Silva Matt J. Kusner Arthur Gretton Krikamol Muandet
+ PDF Chat	Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation	2021	Liyuan Xu Heishiro Kanagawa Arthur Gretton
+	Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction	2021	Afsaneh Mastouri Yuchen Zhu Limor Gultchin Anna Korba Ricardo Silva Matt J. Kusner Arthur Gretton Krikamol Muandet
+	Stein's Method Meets Statistics: A Review of Some Recent Developments	2021	Andreas Anastasiou Alessandro Barp François‐Xavier Briol Bruno Ebner Robert E. Gaunt Fatemeh Ghaderinezhad Jackson Gorham Arthur Gretton Christophe Ley Qiang Liu
+	A Kernel Log-Rank Test of Independence for Right-Censored Data	2021	Tamara Fernández Arthur Gretton David Rindt Dino Sejdinović
+	On Instrumental Variable Regression for Deep Offline Policy Evaluation	2021	Yutian Chen Liyuan Xu Çaǧlar Gülçehre Tom Le Paine Arthur Gretton Nando de Freitas Arnaud Doucet
+	Self-Supervised Learning with Kernel Dependence Maximization	2021	Yazhe Li Roman Pogodin Danica J. Sutherland Arthur Gretton
+	Towards an Understanding of Benign Overfitting in Neural Networks	2021	Li Zhu Zhi‐Hua Zhou Arthur Gretton
+	Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation	2021	Liyuan Xu Heishiro Kanagawa Arthur Gretton
+	Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves	2021	Rahul Singh Liyuan Xu Arthur Gretton
+	Composite Goodness-of-fit Tests with Kernels	2021	Oscar Key Tamara Fernández Arthur Gretton François‐Xavier Briol
+	MMD Aggregated Two-Sample Test	2021	Antonin Schrab Ilmun Kim Mélisande Albert Béatrice Laurent Benjamin Guedj Arthur Gretton
+	KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support	2021	Pierre Glaser Michael Arbel Arthur Gretton
+	Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction	2021	Afsaneh Mastouri Yuchen Zhu Limor Gultchin Anna Korba Ricardo Silva Matt J. Kusner Arthur Gretton Krikamol Muandet
+	Stein's Method Meets Computational Statistics: A Review of Some Recent Developments	2021	Andreas Anastasiou Alessandro Barp François‐Xavier Briol Bruno Ebner Robert E. Gaunt Fatemeh Ghaderinezhad Jackson Gorham Arthur Gretton Christophe Ley Qiang Liu
+	A kernel test for quasi-independence.	2020	Tamara Fernández Wenkai Xu Marc Ditzhaus Arthur Gretton
+ PDF Chat	Learning Deep Features in Instrumental Variable Regression	2020	Liyuan Xu Yutian Chen Siddarth Srinivasan Nando de Freitas Arnaud Doucet Arthur Gretton
+	Kernel Methods for Policy Evaluation: Treatment Effects, Mediation Analysis, and Off-Policy Planning.	2020	Rahul Singh Liyuan Xu Arthur Gretton
+	Reproducing Kernel Methods for Nonparametric and Semiparametric Treatment Effects	2020	Rahul Singh Liyuan Xu Arthur Gretton
+ PDF Chat	Kernel Methods for Causal Functions: Dose Response Curves and Heterogeneous Treatment Effects	2020	Rahul Singh Liyuan Xu Arthur Gretton
+	Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data	2020	Tamara Fernández Nicolás Rivera Wenkai Xu Arthur Gretton
+	Layer-wise Learning of Kernel Dependence Networks	2020	Chieh Wu Aria Masoomi Arthur Gretton Jennifer Dy
+	Kernelized Wasserstein Natural Gradient	2020	Michael Arbel Arthur Gretton Weikai Li Guido Montúfar
+	Generalized Energy Based Models	2020	Michael Arbel Zhou Liang Arthur Gretton
+ PDF Chat	Model-based kernel sum rule: kernel Bayesian inference with probabilistic models	2020	Yu Nishiyama Motonobu Kanagawa Arthur Gretton Kenji Fukumizu
+	Learning Deep Kernels for Non-Parametric Two-Sample Tests	2020	Feng Liu Wenkai Xu Jie Lü Guangquan Zhang Arthur Gretton Danica J. Sutherland
+	Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data	2020	Wenkai Xu Tamara Fernández Nicolás Rivera Arthur Gretton
+	A Non-Asymptotic Analysis for Stein Variational Gradient Descent	2020	Anna Korba Adil Salim Michael Arbel Giulia Luise Arthur Gretton
+	Learning Deep Features in Instrumental Variable Regression	2020	Liyuan Xu Yutian Chen Siddarth Srinivasan Nando de Freitas Arnaud Doucet Arthur Gretton
+	A Non-Asymptotic Analysis for Stein Variational Gradient Descent	2020	Anna Korba Adil Salim Michael Arbel Giulia Luise Arthur Gretton
+	A kernel test for quasi-independence	2020	Tamara Fernández Wenkai Xu Marc Ditzhaus Arthur Gretton
+	Kernel Dependence Network	2020	Chieh Wu Aria Masoomi Arthur Gretton Jennifer Dy
+	A case for new neural network smoothness constraints	2020	Mihaela Rosca Théophane Weber Arthur Gretton Shakir Mohamed
+	Reproducing Kernel Methods for Nonparametric and Semiparametric Treatment Effects	2020	Rahul Singh Liyuan Xu Arthur Gretton
+	Deep Layer-wise Networks Have Closed-Form Weights	2020	Chieh Wu Aria Masoomi Arthur Gretton Jennifer Dy
+	A kernel test for quasi-independence	2020	Tamara Fernández Wenkai Xu Marc Ditzhaus Arthur Gretton
+	Efficient Wasserstein Natural Gradients for Reinforcement Learning	2020	Ted Moskovitz Michael Arbel Ferenc Huszár Arthur Gretton
+	Generalized Energy Based Models	2020	Michael Arbel Liang Zhou Arthur Gretton
+	Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves	2020	Rahul Singh Liyuan Xu Arthur Gretton
+	A Weaker Faithfulness Assumption based on Triple Interactions	2020	Alexander Marx Arthur Gretton Joris M. Mooij
+	Kernel Instrumental Variable Regression	2019	Rahul Singh Maneesh Sahani Arthur Gretton
+	Kernel Instrumental Variable Regression	2019	Rahul Singh Maneesh Sahani Arthur Gretton
+	Exponential Family Estimation via Adversarial Dynamics Embedding	2019	Bo Dai Zhen Liu Hanjun Dai Niao He Arthur Gretton Le Song Dale Schuurmans
+	Kernel exponential family estimation via doubly dual embedding	2019	Bo Dai Hanjun Dai Arthur Gretton Le Song Dale Schuurmans Niao He
+ PDF Chat	Antithetic and Monte Carlo kernel estimators for partial rankings	2019	María Lomelí Mark Rowland Arthur Gretton Zoubin Ghahramani
+	Maximum Mean Discrepancy Gradient Flow	2019	Michael Arbel Anna Korba Adil Salim Arthur Gretton
+	A Kernel Stein Test for Comparing Latent Variable Models	2019	Heishiro Kanagawa Wittawat Jitkrittum Lester Mackey Kenji Fukumizu Arthur Gretton
+	Counterfactual Distribution Regression for Structured Inference	2019	Nicolò Colombo Ricardo Silva Soong Moon Kang Arthur Gretton
+	Exponential Family Estimation via Adversarial Dynamics Embedding	2019	Bo Dai Zhen Liu Hanjun Dai Niao He Arthur Gretton Le Song Dale Schuurmans
+	Kernelized Wasserstein Natural Gradient	2019	Michael Arbel Arthur Gretton Wuchen Li Guido Montúfar
+	A kernel log-rank test of independence for right-censored data	2019	Tamara Fernández Arthur Gretton David Rindt Dino Sejdinović
+	Kernel Instrumental Variable Regression	2019	Rahul Singh Maneesh Sahani Arthur Gretton
+	Informative Features for Model Comparison	2018	Wittawat Jitkrittum Heishiro Kanagawa Patsorn Sangkloy James Hays Bernhard Schölkopf Arthur Gretton
+	Learning deep kernels for exponential family densities	2018	Li Kevin Wenliang Danica J. Sutherland Heiko Strathmann Arthur Gretton
+	A maximum-mean-discrepancy goodness-of-fit test for censored data	2018	Tamara Fernández Arthur Gretton
+	Antithetic and Monte Carlo kernel estimators for partial rankings	2018	María Lomelí Mark Rowland Arthur Gretton Zoubin Ghahramani
+	Efficient and principled score estimation with Nyström kernel exponential families	2018	Danica J. Sutherland Heiko Strathmann Michael Arbel Arthur Gretton
+	A Generative Deep Recurrent Model for Exchangeable Data	2018	Iryna Korshunova Jonas Degrave Ferenc Huszár Yarin Gal Arthur Gretton Joni Dambre
+	Demystifying MMD GANs	2018	Mikołaj Bińkowski Danica J. Sutherland Michael Arbel Arthur Gretton
+	On gradient regularizers for MMD GANs	2018	Michael Arbel Danica J. Sutherland Mikołaj Bińkowski Arthur Gretton
+	Kernel Exponential Family Estimation via Doubly Dual Embedding	2018	Bo Dai Hanjun Dai Arthur Gretton Le Song Dale Schuurmans Niao He
+	Informative Features for Model Comparison	2018	Wittawat Jitkrittum Heishiro Kanagawa Patsorn Sangkloy James Hays Bernhard Schölkopf Arthur Gretton
+	BRUNO: A Deep Recurrent Model for Exchangeable Data	2018	Iryna Korshunova Jonas Degrave Ferenc Huszár Yarin Gal Arthur Gretton Joni Dambre
+	Learning deep kernels for exponential family densities	2018	Li Kevin Wenliang Danica J. Sutherland Heiko Strathmann Arthur Gretton
+	A maximum-mean-discrepancy goodness-of-fit test for censored data	2018	Tamara Fernández Arthur Gretton
+	Antithetic and Monte Carlo kernel estimators for partial rankings	2018	María Lomelí Mark Rowland Arthur Gretton Zoubin Ghahramani
+	Demystifying MMD GANs	2018	Mikołaj Bińkowski Danica J. Sutherland Michael Arbel Arthur Gretton
+ PDF Chat	A Linear-Time Kernel Goodness-of-Fit Test	2017	Wittawat Jitkrittum Wenkai Xu Zoltán Szabó Kenji Fukumizu Arthur Gretton
+	Kernel Conditional Exponential Family.	2017	Michael Arbel Arthur Gretton
+	Density Estimation in Infinite Dimensional Exponential Families	2017	Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Aapo Hyvärinen Revant Kumar
+ PDF Chat	GP-Select: Accelerating EM Using Adaptive Subspace Preselection	2017	Jacquelyn A. Shelton Jan Gasthaus Zhenwen Dai Jörg Lücke Arthur Gretton
+	Efficient and principled score estimation.	2017	Danica J. Sutherland Heiko Strathmann Michael Arbel Arthur Gretton
+	Efficient and principled score estimation with Nystr\"om kernel exponential families	2017	Danica J. Sutherland Heiko Strathmann Michael Arbel Arthur Gretton
+ PDF Chat	Large-scale kernel methods for independence testing	2017	Qinyi Zhang Sarah Filippi Arthur Gretton Dino Sejdinović
+	A Linear-Time Kernel Goodness-of-Fit Test	2017	Wittawat Jitkrittum Wenkai Xu Zoltán Szabó Kenji Fukumizu Arthur Gretton
+	Kernel Conditional Exponential Family	2017	Michael Arbel Arthur Gretton
+	Efficient and principled score estimation with Nyström kernel exponential families	2017	Danica J. Sutherland Heiko Strathmann Michael Arbel Arthur Gretton
+	Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy	2016	Danica J. Sutherland Hsiao-Yu Fish Tung Heiko Strathmann Soumyajit De Aaditya Ramdas Alex Smola Arthur Gretton
+ PDF Chat	MERLiN: Mixture Effect Recovery in Linear Networks	2016	Sebastian Weichwald Moritz Grosse‐Wentrup Arthur Gretton
+	Kernel techniques for adaptive Monte Carlo methods	2016	Heiko Strathmann Dino Sejdinović Samuel A. Livingston Ingmar Schuster Maria Lomeli Garcia Zoltán Szabó Christophe Andrieu Arthur Gretton
+	A kernel test for three-variable interactions with random processes	2016	Paul K. Rubenstein Kacper Chwialkowski Arthur Gretton
+	A kernel test of goodness of fit	2016	Kacper Chwialkowski Heiko Strathmann Arthur Gretton
+ PDF Chat	Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data	2016	Sebastian Weichwald Arthur Gretton Bernhard Schölkopf Moritz Grosse‐Wentrup
+	Interpretable Distribution Features with Maximum Testing Power	2016	Wittawat Jitkrittum Zoltán Szabó Kacper Chwialkowski Arthur Gretton
+	Distribution Regression with Minimax-Optimal Guarantee	2016	Zoltán Szabó B Sriperumbudur Barnabás Póczos Arthur Gretton
+	A Kernel Test of Goodness of Fit	2016	Kacper Chwialkowski Heiko Strathmann Arthur Gretton
+	A Kernel Test for Three-Variable Interactions with Random Processes	2016	Paul K. Rubenstein Kacper Chwialkowski Arthur Gretton
+	Fast Non-Parametric Tests of Relative Dependency and Similarity	2016	Wacha Bounliphone Eugene Belilovsky Arthur Tenenhaus Ioannis Antonoglou Arthur Gretton Matthew B. Blashcko
+	Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy	2016	Danica J. Sutherland Hsiao-Yu Fish Tung Heiko Strathmann Soumyajit De Aaditya Ramdas Alex Smola Arthur Gretton
+	An Adaptive Test of Independence with Analytic Kernel Embeddings	2016	Wittawat Jitkrittum Zoltán Szabó Arthur Gretton
+	Kernel mean shrinkage estimators	2016	Krikamol Muandet Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Bernhard Schölkopf
+	Learning theory for distribution regression	2016	Zoltán Szabó Bharath K. Sriperumbudur Barnabás Póczos Arthur Gretton
+	Interpretable Distribution Features with Maximum Testing Power	2016	Wittawat Jitkrittum Zoltán Szabó Kacper Chwialkowski Arthur Gretton
+	Interpretable Distribution Features with Maximum Testing Power	2016	Wittawat Jitkrittum Zoltán Szabó Kacper Chwialkowski Arthur Gretton
+	A Kernel Test of Goodness of Fit	2016	Kacper Chwialkowski Heiko Strathmann Arthur Gretton
+ PDF Chat	Filtering with State-Observation Examples via Kernel Monte Carlo Filter	2015	Motonobu Kanagawa Yu Nishiyama Arthur Gretton Kenji Fukumizu
+	Learning Theory for Vector-Valued Distribution Regression	2015	Zoltán Szabó B Sriperumbudur Barnabás Póczos Arthur Gretton
+	Fast two-sample testing with analytic representations of probability measures	2015	Kacper Chwialkowski Aaditya Ramdas Dino Sejdinović Arthur Gretton
+	Gradient-free Hamiltonian Monte Carlo with efficient kernel exponential families	2015	Heiko Strathmann Dino Sejdinović Samuel Livingstone Zoltán Szabó Arthur Gretton
+	Distribution Regression: Computational and Statistical Tradeoffs	2015	Zoltán Szabó B Sriperumbudur Barnabás Póczos Arthur Gretton
+	A Test of Relative Similarity	2015	Wacha Bounliphone Eugene Belilovsky Matthew B. Blaschko Ioannis Antonoglou Arthur Gretton
+	Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages	2015	Wittawat Jitkrittum Arthur Gretton Nicolas Heess S. M. Ali Eslami Balaji Lakshminarayanan Dino Sejdinović Zoltán Szabó
+	Consistent Vector-valued Distribution Regression	2015	Zoltán Szabó Arthur Gretton Barnabás Póczos B Sriperumbudur
+	Passing Expectation Propagation Messages with Kernel Methods	2015	Wittawat Jitkrittum Arthur Gretton Nicolas Heess
+	A simpler condition for consistency of a kernel independence test	2015	Arthur Gretton
+	A Test of Relative Similarity For Model Selection in Generative Models	2015	Wacha Bounliphone Eugene Belilovsky Matthew B. Blaschko Ioannis Antonoglou Arthur Gretton
+	Fast two-sample testing with analytic representations of probability measures	2015	Kacper Chwialkowski Aaditya Ramdas Dino Sejdinović Arthur Gretton
+	Fast Two-Sample Testing with Analytic Representations of Probability Measures	2015	Kacper Chwialkowski Aaditya Ramdas Dino Sejdinović Arthur Gretton
+	Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families	2015	Heiko Strathmann Dino Sejdinović Samuel Livingstone Zoltán Szabó Arthur Gretton
+	Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages	2015	Wittawat Jitkrittum Arthur Gretton Nicolas Heess S. M. Ali Eslami Balaji Lakshminarayanan Dino Sejdinović Zoltán Szabó
+	Passing Expectation Propagation Messages with Kernel Methods	2015	Wittawat Jitkrittum Arthur Gretton Nicolas Heess
+	Kernel non-parametric tests of relative dependency	2014	Wacha Bounliphone Arthur Gretton Matthew B. Blaschko
+	GP-select: Accelerating EM using adaptive subspace preselection	2014	Jacquelyn A. Shelton Jan Gasthaus Zhenwen Dai Joerg Luecke Arthur Gretton
+	A Wild Bootstrap for Degenerate Kernel Tests	2014	Kacper Chwialkowski Dino Sejdinović Arthur Gretton
+	Learning Theory for Distribution Regression	2014	Zoltán Szabó Bharath K. Sriperumbudur Barnabás Póczos Arthur Gretton
+	Model-based Kernel Sum Rule	2014	Yu Nishiyama Motonobu Kanagawa Arthur Gretton Kenji Fukumizu
+	Simple consistent distribution regression on compact metric domains	2014	Zoltán Szabó Arthur Gretton Barnabás Póczos B Sriperumbudur
+	A Wild Bootstrap for Degenerate Kernel Tests	2014	Kacper Chwialkowski Dino Sejdinović Arthur Gretton
+	Kernel Adaptive Metropolis-Hastings	2014	Dino Sejdinović Heiko Strathmann Maria Lomeli Garcia Christophe Andrieu Arthur Gretton
+	Distribution Regression - the Set Kernel Heuristic is Consistent	2014	Zoltán Szabó Arthur Gretton Barnabás Póczos B Sriperumbudur
+	A Kernel Independence Test for Random Processes	2014	Kacper Chwialkowski Arthur Gretton
+	Consistent, Two-Stage Sampled Distribution Regression via Mean Embedding.	2014	Zoltán Szabó Arthur Gretton Barnabás Póczos Bharath K. Sriperumbudur
+	A Kernel Independence Test for Random Processes	2014	Kacper Chwialkowski Arthur Gretton
+	Kernel Mean Shrinkage Estimators	2014	Krikamol Muandet Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Bernhard Schölkopf
+	Two-stage Sampled Learning Theory on Distributions	2014	Zoltán Szabó Arthur Gretton Barnabás Póczos Bharath K. Sriperumbudur
+	A low variance consistent test of relative dependency	2014	Wacha Bounliphone Arthur Gretton Arthur Tenenhaus Matthew B. Blaschko
+	Dependent Pairs of Maximum Mean Descrepancy Tests	2014	Ioannis Antonoglou Matthew B. Blaschko Arthur Gretton
+	Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models	2014	Yu Nishiyama Motonobu Kanagawa Arthur Gretton Kenji Fukumizu
+	Learning Theory for Distribution Regression	2014	Zoltán Szabó Bharath K. Sriperumbudur Barnabás Póczos Arthur Gretton
+	A Wild Bootstrap for Degenerate Kernel Tests	2014	Kacper Chwialkowski Dino Sejdinović Arthur Gretton
+	Kernel Monte Carlo Filter	2013	Motonobu Kanagawa Yu Nishiyama Arthur Gretton Kenji Fukumizu
+	A Kernel Test for Three-Variable Interactions	2013	Dino Sejdinović Arthur Gretton Wicher Bergsma
+	B -tests: low variance kernel two-sample tests	2013	Wojciech Zaremba Arthur Gretton Matthew B. Blaschko
+ PDF Chat	B-tests: Low Variance Kernel Two-Sample Tests	2013	Wojciech Zaremba Arthur Gretton Matthew B. Blaschko
+	Equivalence of distance-based and RKHS-based statistics in hypothesis testing	2013	Dino Sejdinović Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu
+	B-test: A Non-parametric, Low Variance Kernel Two-sample Test	2013	Wojciech Zaremba Arthur Gretton Matthew B. Blaschko
+	Smooth Operators	2013	Steffen Grünewälder Arthur Gretton John Shawe‐Taylor
+	A Kernel Test for Three-Variable Interactions	2013	Dino Sejdinović Arthur Gretton Wicher Bergsma
+	Kernel Mean Estimation and Stein's Effect	2013	Krikamol Muandet Kenji Fukumizu Bharath K. Sriperumbudur Arthur Gretton Bernhard Schölkopf
+	Density Estimation in Infinite Dimensional Exponential Families	2013	Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Aapo Hyvärinen Revant Kumar
+	B-tests: Low Variance Kernel Two-Sample Tests	2013	Wojciech Zaremba Arthur Gretton Matthew B. Blaschko
+	B-test: A Non-parametric, Low Variance Kernel Two-sample Test	2013	Wojciech Zaremba Arthur Gretton Matthew B. Blaschko
+	Kernel Bayes' rule: Bayesian inference with positive definite kernels	2013	Kenji Fukumizu Le Song Arthur Gretton
+	Kernel Adaptive Metropolis-Hastings	2013	Dino Sejdinović Heiko Strathmann Maria Lomeli Garcia Christophe Andrieu Arthur Gretton
+	Filtering with State-Observation Examples via Kernel Monte Carlo Filter	2013	Motonobu Kanagawa Yu Nishiyama Arthur Gretton Kenji Fukumizu
+	Hilbert Space Embeddings of Predictive State Representations	2013	Byron Boots Geoffrey J. Gordon Arthur Gretton
+	Kernel Mean Estimation and Stein's Effect	2013	Krikamol Muandet Kenji Fukumizu Bharath K. Sriperumbudur Arthur Gretton Bernhard Schölkopf
+	A Kernel Test for Three-Variable Interactions	2013	Dino Sejdinović Arthur Gretton Wicher Bergsma
+	Optimal kernel choice for large-scale two-sample tests	2012	Arthur Gretton Dino Sejdinović Heiko Strathmann Sivaraman Balakrishnan Massimiliano Pontil Kenji Fukumizu Bharath K. Sriperumbudur
+	Hilbert space embeddings of POMDPs	2012	Yu Nishiyama Abdeslam Boularias Arthur Gretton Kenji Fukumizu
+	Modelling transition dynamics in MDPs with RKHS embeddings	2012	Guy Lever Luca Baldassarre Arthur Gretton Massimiliano Pontil Steffen Gr new lder
+	Hypothesis testing using pairwise distances and associated kernels	2012	Dino Sejdinović Arthur Gretton Kenji Fukumizu Bharath K. Sriperumbudur
+	Modelling transition dynamics in MDPs with RKHS embeddings	2012	Steffen Grünewälder Guy Lever Luca Baldassarre Massi Pontil Arthur Gretton
+	Hypothesis testing using pairwise distances and associated kernels	2012	Dino Sejdinović Arthur Gretton Bharath K. Sriperumbudur Kenji Fukumizu
+	A kernel two-sample test	2012	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola
+	Conditional mean embeddings as regressors - supplementary	2012	Steffen Grünewälder Guy Lever Luca Baldassarre Sam Patterson Arthur Gretton Massimiliano Pontil
+	Hypothesis testing using pairwise distances and associated kernels (with Appendix)	2012	Dino Sejdinović Arthur Gretton Bharath K. Sriperumbudur Kenji Fukumizu
+ PDF Chat	On the empirical estimation of integral probability metrics	2012	Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Bernhard Schölkopf Gert Lanckriet
+	Hilbert Space Embeddings of POMDPs	2012	Yu Nishiyama Abdeslam Boularias Arthur Gretton Kenji Fukumizu
+	Modelling transition dynamics in MDPs with RKHS embeddings	2012	Steffen Grünewälder Guy Lever Luca Baldassarre Massi Pontil Arthur Gretton
+	Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees	2011	Joseph E. Gonzalez Yucheng Low Arthur Gretton Carlos Guestrin
+	Kernel Belief Propagation	2011	Le Song Arthur Gretton Danny Bickson Yucheng Low Carlos Guestrin
+	Modeling transition dynamics in MDPs with RKHS embeddings of conditional distributions	2011	Steffen Grünewälder Luca Baldassarre Massimiliano Pontil Arthur Gretton Guy Lever
+	Kernel Belief Propagation	2011	Le Song Arthur Gretton Danny Bickson Yucheng Low Carlos Guestrin
+	Kernel Bayes' rule	2010	Kenji Fukumizu Le Song Arthur Gretton
+	Non-parametric estimation of integral probability metrics	2010	Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Bernhard Schölkopf Gert Lanckriet
+	Hilbert Space Embeddings and Metrics on Probability Measures	2010	Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu Bernhard Schölkopf Gert Lanckriet
+	Consistent Nonparametric Tests of Independence	2010	Arthur Gretton László Györfi
+	Kernel Bayes' rule	2010	Kenji Fukumizu Le Song Arthur Gretton
+	A Fast, Consistent Kernel Two-Sample Test	2009	Arthur Gretton Kenji Fukumizu Zaïd Harchaoui Bharath K. Sriperumbudur
+	Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions	2009	Kenji Fukumizu Arthur Gretton Gert Lanckriet Bernhard Schölkopf Bharath K. Sriperumbudur
+ PDF Chat	Discussion of: Brownian distance covariance	2009	Arthur Gretton Kenji Fukumizu Bharath K. Sriperumbudur
+	Hilbert space embeddings and metrics on probability measures	2009	Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu Bernhard Schölkopf Gert Lanckriet
+	A note on integral probability metrics and $\phi$-divergences	2009	Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu Gert Lanckriet Bernhard Schölkopf
+	On integral probability metrics, ϕ-divergences and binary classification	2009	Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Bernhard Schölkopf Gert Lanckriet
+	Hilbert space embeddings and metrics on probability measures	2009	Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu Bernhard Schölkopf Gert Lanckriet
+ PDF Chat	Nonparametric Independence Tests: Space Partitioning and Kernel Approaches	2008	Arthur Gretton László Györfi
+	A Kernel Method for the Two-Sample Problem	2008	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola
+	Kernel Measures of Conditional Dependence	2007	Kenji Fukumizu Arthur Gretton Xiaohai Sun Bernhard Schölkopf
+	Hilbert Space Representations of Probability Distributions	2007	Arthur Gretton
+ PDF Chat	A Kernel Method for the Two-Sample-Problem	2007	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola
+	A kernel approach to comparing distributions	2007	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola
+	Supervised Feature Selection via Dependence Estimation	2007	Le Song Alex Smola Arthur Gretton Karsten Borgwardt Justin Bedő
+	Kernel Methods for Measuring Independence	2005	Arthur Gretton Ralf Herbrich Alexander J. Smola Olivier Bousquet Bernhard Schölkopf
+	Behaviour and Convergence of the Constrained Covariance	2004	Arthur Gretton Bousquet Smola A Schölkopf Herbrich R NK Logothetis
+ PDF Chat	The kernel mutual information	2004	Arthur Gretton Ralf Herbrich Alex Smola

Common Coauthors

Coauthor	Papers Together
Kenji Fukumizu	37
Dino Sejdinović	28
Bharath K. Sriperumbudur	27
Zoltán Szabó	21
Bernhard Schölkopf	21
Michael Arbel	20
Heiko Strathmann	17
Danica J. Sutherland	16
Wittawat Jitkrittum	16
Kacper Chwialkowski	16
Tamara Fernández	12
Barnabás Póczos	11
Antonin Schrab	10
Liyuan Xu	10
Matthew B. Blaschko	10
Yu Nishiyama	8
Heishiro Kanagawa	8
Gert Lanckriet	8
Krikamol Muandet	8
Arnaud Doucet	7
Anna Korba	7
Rahul Singh	7
Liyuan Xu	6
B Sriperumbudur	6
Dimitri Meunier	6
Le Song	6
Lester Mackey	6
Motonobu Kanagawa	6
Matt J. Kusner	6
François‐Xavier Briol	6
Aaditya Ramdas	5
Steffen Grünewälder	5
Wenkai Xu	5
Wojciech Zaremba	5
Rahul Singh	5
Benjamin Guedj	5
Guy Lever	5
Karsten Borgwardt	5
Luca Baldassarre	5
Wacha Bounliphone	5
Alexander J. Smola	5
Alex Smola	4
Aria Masoomi	4
Le Song	4
Massimiliano Pontil	4
Ioannis Antonoglou	4
Dale Schuurmans	4
Roman Pogodin	4
Niao He	4
Malte J. Rasch	4

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	A kernel two-sample test	2012	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola	48
+	Hilbert Space Embeddings and Metrics on Probability Measures	2010	Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu Bernhard Schölkopf Gert Lanckriet	41
+	Kernel Measures of Conditional Dependence	2007	Kenji Fukumizu Arthur Gretton Xiaohai Sun Bernhard Schölkopf	40
+ PDF Chat	Dimensionality Reduction for Supervised Learning With Reproducing Kernel Hilbert Spaces	2003	Kenji Fukumizu Francis R. Bach Michael I. Jordan	29
+	Integral Probability Metrics and Their Generating Classes of Functions	1997	Alfred Müller	24
+ PDF Chat	A Kernel Method for the Two-Sample-Problem	2007	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola	23
+	Optimal kernel choice for large-scale two-sample tests	2012	Arthur Gretton Dino Sejdinović Heiko Strathmann Sivaraman Balakrishnan Massimiliano Pontil Kenji Fukumizu Bharath K. Sriperumbudur	18
+	Real Analysis and Probability	1972		16
+ PDF Chat	Measuring and testing dependence by correlation of distances	2007	Gábor J. Székely Maria L. Rizzo Н. К. Бакиров	16
+	A Fast, Consistent Kernel Two-Sample Test	2009	Arthur Gretton Kenji Fukumizu Zaïd Harchaoui Bharath K. Sriperumbudur	15
+	Equivalence of distance-based and RKHS-based statistics in hypothesis testing	2013	Dino Sejdinović Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu	15
+ PDF Chat	Joint measures and cross-covariance operators	1973	C. Richard Baker	14
+	Consistent Nonparametric Tests of Independence	2010	Arthur Gretton László Györfi	13
+	Kernel-based Conditional Independence Test and Application in Causal Discovery	2012	Kun Zhang Jonas Peters Dominik Janzing Bernhard Schölkopf	13
+	Efficient svm training using low-rank kernel representations	2002	Shai Fine Katya Scheinberg	12
+	Kernel Methods for Measuring Independence	2005	Arthur Gretton Ralf Herbrich Alexander J. Smola Olivier Bousquet Bernhard Schölkopf	12
+	Distance covariance in metric spaces	2013	Russell Lyons	11
+	Kernel Belief Propagation	2011	Le Song Arthur Gretton Danny Bickson Yucheng Low Carlos Guestrin	11
+	A Consistent Test for Bivariate Dependence	1993	Andrey Feuerverger	11
+ PDF Chat	Optimal Rates for the Regularized Least-Squares Algorithm	2006	Andrea Caponnetto Ernesto De Vito	11
+	Testing for Homogeneity with Kernel Fisher Discriminant Analysis	2008	Zaïd Harchaoui Francis Bach Éric Moulines	11
+	Two-Sample Test Statistics for Measuring Discrepancies Between Two Multivariate Probability Density Functions Using Kernel-Based Density Estimates	1994	Niall Anderson Peter A. Hall D. M. Titterington	11
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	10
+	Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions	2009	Kenji Fukumizu Arthur Gretton Gert Lanckriet Bernhard Schölkopf Bharath K. Sriperumbudur	10
+ PDF Chat	Chapter 77 Linear Inverse Problems in Structural Econometrics Estimation Based on Spectral Decomposition and Regularization	2007	Marine Carrasco Jean‐Pierre Florens Èric Renault	9
+	On a new multivariate two-sample test	2003	Ludwig Baringhaus Carsten Franz	9
+ PDF Chat	Kernel dimension reduction in regression	2009	Kenji Fukumizu Francis Bach Michael I. Jordan	8
+ PDF Chat	On the empirical estimation of integral probability metrics	2012	Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Bernhard Schölkopf Gert Lanckriet	8
+	Dependent wild bootstrap for degenerate<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si65.gif" display="inline" overflow="scroll"><mml:mi>U</mml:mi></mml:math>- and<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si66.gif" display="inline" overflow="scroll"><mml:mi>V</mml:mi></mml:math>-statistics	2013	Anne Leucht Michael H. Neumann	8
+ PDF Chat	Multivariate Generalizations of the Wald-Wolfowitz and Smirnov Two-Sample Tests	1979	Jerome H. Friedman Lawrence C. Rafsky	8
+ PDF Chat	On the Bootstrap of $U$ and $V$ Statistics	1992	Miguel A. Arcones Evarist Giné	8
+	A Kernel Test for Three-Variable Interactions	2013	Dino Sejdinović Arthur Gretton Wicher Bergsma	8
+	A Kernel Method for the Two-Sample Problem	2008	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola	8
+	Density Estimation in Infinite Dimensional Exponential Families	2017	Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Aapo Hyvärinen Revant Kumar	8
+	Harmonic Analysis on Semigroups	1984	Christian Berg Jens Peter Christensen Paul Ressel	8
+ PDF Chat	Learning Theory Estimates via Integral Operators and Their Approximations	2007	Steve Smale Ding‐Xuan Zhou	8
+	Consistent testing of total independence based on the empirical characteristic function	1995	Annaliisa Kankainen	8
+ PDF Chat	Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization	2010	XuanLong Nguyen Martin J. Wainwright Michael I. Jordan	8
+ PDF Chat	A Class of Statistics with Asymptotically Normal Distribution	1992	Wassily Hoeffding	7
+	Kernel Instrumental Variable Regression	2019	Rahul Singh Maneesh Sahani Arthur Gretton	7
+	A new test for multivariate normality	2004	Gábor J. Székely Maria L. Rizzo	7
+	On the method of bounded differences	1989	Colin McDiarmid	7
+	Mercer’s Theorem on General Domains: On the Interaction between Measures, Kernels, and RKHSs	2012	Ingo Steinwart Clint Scovel	7
+	A kernel test of goodness of fit	2016	Kacper Chwialkowski Heiko Strathmann Arthur Gretton	7
+	Density Estimation in Infinite Dimensional Exponential Families	2013	Bharath K. Sriperumbudur Kenji Fukumizu Arthur Gretton Aapo Hyvärinen Revant Kumar	7
+	Spectral Normalization for Generative Adversarial Networks	2018	Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida	7
+ PDF Chat	Brownian distance covariance	2009	Gábor J. Székely Maria L. Rizzo	7
+	f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization	2016	Sebastian Nowozin Botond Cseke Ryota Tomioka	7
+ PDF Chat	VECTOR VALUED REPRODUCING KERNEL HILBERT SPACES AND UNIVERSALITY	2010	Claudio Carmeli Ernesto De Vito Alessandro Toigo Veronica Umanità	7
+	Weak Convergence and Empirical Processes	1996	Aad van der Vaart Jon A. Wellner	7